Welcome to my GitHub repository for the "Data Science Capstone for Winning the Space Race" capstone project.
Here, I've tackled the exciting world of commercial space travel, focusing on the innovation of reusable rockets by companies like SpaceX.
My goal was to analyze launch data, build dashboards, and use machine learning to predict launch costs, helping a hypothetical company, Space Y, challenge SpaceX's dominance.
- Data Collection API: Utilize APIs to gather data on space launches, focusing on parameters critical for analysis.
- Data Collection with Web Scraping: Extract data from web sources that are essential for understanding the space launch landscape.
- Data Wrangling: Clean and prepare the collected data for analysis, ensuring it's accurate and usable.
- EDA with SQL: Conduct exploratory data analysis using SQL to uncover patterns and insights from the data.
- EDA with Visualization: Use various visualization tools to explore the data further and uncover hidden trends.
- Interactive Dashboard with Plotly Dash: Develop interactive dashboards to display your findings dynamically, making the data accessible to non-technical stakeholders.
- Interactive Visual Analytics with Folium: Utilize Folium for geospatial analysis, offering a geographical perspective on launch sites and their outcomes.
- Machine Learning Prediction: Build a machine learning model to predict whether the first stage of Falcon 9 will land successfully, influencing the cost estimation of launches.
- Comprehensive data analysis from gathering to predictive modeling.
- Practical Python/SQL application using libraries for data manipulation, visualization, and machine learning.
- Creating interactive tools for data presentation.
- A detailed methodology, analysis, and insights report.
- A repository with all project code and documentation.
- An interactive dashboard showcasing analysis and predictions.
- A presentation for both technical and non-technical audiences.
This project was my deep dive into data science within the commercial space industry, blending my passion for space exploration with data analysis and machine learning.